Open AccessEarly Prediction of COVID-19 Ventilation Requirement and Mortality from Routinely Collected Baseline Chest Radiographs, Laboratory, and Clinical Data with Machine Learning
Author(s) -
Abdulrhman Aljouie,
Ahmed Almazroa,
Yahya Bokhari,
Mohammed Alawad,
Ebrahim Mahmoud,
Eman Alawad,
Ali Alsehawi,
Mamoon Rashid,
Lamya Alomair,
Shahad Almozaai,
Bedoor Albesher,
Hassan Alomaish,
Rayyan Daghistani,
Naif Khalaf Alharbi,
Manal Alaamery,
Mohammad Bosaeed,
Hesham Alshaalan
Publication year - 2021
Publication title -
journal of multidisciplinary healthcare
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.65
H-Index - 30
ISSN - 1178-2390
DOI - 10.2147/jmdh.s322431
Subject(s) - medicine , covid-19 , emergency medicine , triage , mechanical ventilation , clinical endpoint , predictive modelling , machine learning , clinical trial , disease , computer science , infectious disease (medical specialty)
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan, China, in late 2019 and created a global pandemic that overwhelmed healthcare systems. COVID-19, as of July 3, 2021, yielded 182 million confirmed cases and 3.9 million deaths globally according to the World Health Organization. Several patients who were initially diagnosed with mild or moderate COVID-19 later deteriorated and were reclassified to severe disease type.